Place of work: remote + occasionally one of the EPAM offices in Poland
Contract of employment or B2B contract
EPAM's Data & AI Practice is hiring a Senior Manager - AI & Data Consulting to help our customers craft Analytics and AI strategies, design best-in-class Data & AI platforms, and lead the AI-driven transformation of their enterprises. You'll work shoulder-to-shoulder with industry leaders, translating cutting-edge capabilities (GenAI, agentic systems, ML, advanced analytics) into products that move the needle. We're passionate about delivering measurable value from data and AI, and we're looking for people who share that mindset.
What makes this role different: you won't just advise — you'll own outcomes, shape product strategy at the senior stakeholder level, build and lead high-caliber teams, and have direct influence on how some of the world's largest companies adopt AI responsibly and effectively.
Responsibilities
-
Engage with customer business stakeholders to discover data, analytics, and AI opportunities — from platform to analytics to GenAI and agentic use cases
-
Design and drive executive workshops and stakeholder interviews to define and prioritize strategic and immediate needs
-
Map customer vision and requirements to specific data products, AI products, platforms, and solutions, applying the right product management techniques to each
-
Define success measures with the client at the outset and track realised value after go-live, including adoption levels and the change management needed to reach them
-
Manage consulting engagements end-to-end, owning delivery output, quality and client satisfaction
-
Define human oversight for AI products — review points, confidence thresholds, escalation paths, and the operational effort these require at production volume
-
Assemble and lead multidisciplinary teams of EPAM analysts, data scientists, and engineers to deliver MVPs and production-grade products
-
Act as a data and AI advocate, removing business, technical, and organizational roadblocks
-
Mentor and coach clients and team members on data, analytics, and AI product best practices
-
Partner with account managers to build, grow, and retain strategic customer relationships
-
Work with the business development team on proposals and pitches, including AI-focused opportunities
-
Respond to RFXs, create compelling proposals, and present them to potential clients
Requirements
-
10+ years of total experience in the data, analytics, and/or AI domain
-
3+ years in product, delivery, consulting, or presales roles
-
Preferred: 5+ years in one of our core industries (Life Sciences, CPG & Retail, Energy & Utilities, Financial Services, Automotive), or a track record of working with clients in those sectors
-
Demonstrated experience managing data products for enterprises — including data platforms, data warehouses, data lakes, BI, and advanced analytics solutions — across the full product lifecycle
-
Demonstrated experience managing AI products and a clear understanding of how they differ from analytics products, including:
-
Designing for probabilistic, non-deterministic outputs and managing user expectations accordingly
-
Defining evaluation strategies (offline and online), benchmarks, and quality metrics for ML and GenAI systems, incl. translation to business-meaningful metrics
-
Oversee the model lifecycle (data → training/fine-tuning → evaluation → deployment → monitoring → retraining)
-
Scoping and shipping GenAI use cases (RAG, agents, copilots, summarization, extraction) with awareness of cost, latency, and accuracy trade-offs
-
Applying responsible AI principles — bias mitigation, explainability, human-in-the-loop, governance, and regulatory considerations
-
Managing prompt engineering, evaluation harnesses, and continuous improvement loops as first-class product activities
-
Familiarity with the modern AI stack and ecosystem (foundation models, vector databases, orchestration frameworks, MLOps/LLMOps tooling, evaluation platforms)
-
Ability to facilitate and drive strategy discussions at executive level, including value articulation and tracking of value realization
-
Experience working with end-users driving product design, running UATs, and facilitating and measuring adoption
-
Ability to participate in and influence solution and AI architecture design discussions
-
Solid knowledge of the data, analytics, and AI landscape and recent trends
-
Experience in end-to-end project delivery as part of the team: Cloud Data Platforms, BI/Reporting, Data Catalog / Marketplace, Analytics Migration & Modernization, Predictive Analytics & ML, Generative AI, and Agentic Systems
-
Practical experience designing human-in-the-loop review into production AI systems, including the trade-off between oversight coverage and operational cost